A Deep Reinforced Model for Abstractive Summarization
Attentional, RNN-based encoder-decoder models for abstractive summarization have achieved good performance on short input and output sequences. For longer documents and summaries however these models often include repetitive and incoherent phrases. We introduce a neural network model with a novel intra-attention that attends over the input and continuously generated output separately, and a new tr
Bayesian Deep Learning Workshop | NeurIPS 2021
Schedule The start and end times are 11am -- 7pm GMT / 12pm -- 8pm CET / 6am -- 2pm EST / 3am - 11am PST / 8pm -- 4am JST. Our friends in the Americas are welcome to join the latter sessions, and our friends in eastern time zones are welcome to join the earlier sessions. The schedule interleaves invited speakers, contributed talks, and gather.town poster presentations to allow for networking and s
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